rasbt--python-machine-learning-book
wehub-resource-sync
12 行
731 B
TeX
12 行
731 B
TeX
Introducing a simple linear regression model
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Exploring the Housing Dataset
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Visualizing the important characteristics of a dataset
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Implementing an ordinary least squares linear regression model
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Solving regression for regression parameters with gradient descent
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Estimating the coefficient of a regression model via scikit-learn
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Fitting a robust regression model using RANSAC
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Evaluating the performance of linear regression models
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Using regularized methods for regression
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Turning a linear regression model into a curve – polynomial regression
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Modeling nonlinear relationships in the Housing Dataset
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Dealing with nonlinear relationships using random forests
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Decision tree regression
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Random forest regression
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Summary |